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Bank and Credit Card Reconciliations

Match high-volume bank and card transactions with FloQast AI Matching

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What the source describes

FloQast describes AI Transaction Matching that matches high-volume transactions across multiple data sources, including bank and credit card reconciliations and 3-way matching. Users design matching rules in natural language and adjust them in an interactive interface without IT support, while automated alerts flag unmatched items and an audit trail records all matching activity.

Result or outcome

According to the source, a customer accounting manager said that in the first month they finished reconciling by 3 p.m. on day 1, by noon in the second month, and started day 1 with 80% of matches already matched.

How to run it

  1. Connect the bank or card data source and the general ledger in FloQast so AI Transaction Matching can compare them in one place.
  2. Use the prompt on this page with a small sample of bank and GL lines to draft ranked, plain-language matching rules and test them.
  3. Enter the approved rules in natural language in FloQast and adjust them in the interactive interface until sample results look right.
  4. Run matching, then work the unmatched items that automated alerts flag, routing each one to the person who can resolve it.
  5. Check the audit trail of matching activity and confirm all exceptions are cleared before signing off the reconciliation.

Try it yourself

Copyable prompt

Help me design matching rules for reconciling [bank or card account] to the general ledger. Here is a sample of 30 bank lines and 30 GL lines with their columns. Propose a ranked set of plain-language rules, starting with exact matches (amount and reference) and moving to looser ones (amount within [tolerance], date within [number] days, description contains vendor name). For each rule, state the fields used, the risk of false matches, and whether it should auto-match or only suggest. Then apply the rules to the sample and show which lines remain as exceptions.

[paste bank sample]
[paste GL sample]

Replace the [bracketed] placeholders. Remove client names, account numbers, and personal data before pasting into any AI tool.

What to review

Test looser rules, such as amount tolerances or date windows, against known transactions before letting them auto-match, since they can pair the wrong items. Review a sample of matched lines each month, not just the exceptions. Remove account numbers and customer names from the sample before pasting it into a general AI tool, and treat the customer result FloQast quotes as the vendor's own example.

Related free download: Bank Reconciliation Cheat Sheet (Printable cheat sheet (PDF))

Source: FloQast (product page)

Not professional advice. This is general information, not accounting, tax, legal or financial advice. Check AI output yourself and consult a licensed professional for your situation. See our Terms of Use.

This entry summarizes a public source. Features, plans, and availability change, so confirm details with the vendor. Tool names are trademarks of their respective owners.

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